Purpose-Driven Personalization Technology

Summit Automated Personalization™, Sagarmatha’s proprietary data mining application, has been developed and fine-tuned for over 15 years to reach deep into the masses of consumer behavioral data collected and stored in retailer data warehouses. Summit uses advanced predictive analytics to analyze both historical and ongoing individual customer behavior, learning what, when and where each customer buys, and inferring what they’re likely buying at other stores.

This enables us to understand consumer behavior on an individual shopper level. With this highly-granular knowledge, we tailor the right set of offers for each individual, at any given point in time, optimized per communication channel or touch point.

Our unmatched level of automation enables retailers to run high-frequency personalized promotion cycles – in-sync with actual customer shopping habits and regardless of the number of consumers or the size of potential offer pool. And we do this all without the need for an in-house team of dedicated data mining experts.

Offers
Ranks each offer by popularity, affinities, seasonality, discount attractiveness and more.
Relevancy
Determines the probability purchase, based on individual history and “look alike” concept.
Basket Effect
Predicts the incremental contribution to the basket for each offer redeemed.
Past Engagement
Self learning improves targeting by continuously calibrating based on prior engagements.
Shoppers
Scores each shopper by RFM+, price sensitivity, demographics and more.
Campaign Optimizer
Selects households, offers per household, and communication channels per campaign, based on input from all 10 modules.

Enables issuance and redemption budget management.
Targeting Rules
Enables rule based targeting and constraints to be added manually.
Stores
Determines product availability by store, shoppers main store and more.
Timing
Estimates the optimal offer timing based on individual and average purchase cycles.
Brand Loyalty
Determines shopper loyalty to each brand, loyalty to competing brands, propensity to switch etc.
Channels
Determines the probability that a shopper will be exposed to each offer per channel.

The Science of Third Generation Data Mining

Sagarmatha’s Summit, a third generation data mining solution, eliminates the lengthy and expensive implementation process associated with prior generation software.

First generation data mining tools were manageable exclusively by data analysis experts. And while second generation tools did not require the same data mining expertise, they were still primarily used as “closed reporting tools” with limited functionality.

As a third generation data mining engine, Summit was built from the ground up to optimize targeted marketing in mass retail environments. It was designed specifically to mine vast quantities of customer-level behavioral data, and to rapidly score each and every shopper on a range of advanced Recency-Frequency-Monetary (RFM+) metrics. Summit’s constantly-evolving algorithms then match each shopper with the most appropriate set of offers from any available source, and determine the most suitable channels by which to communicate with them.

Additional Summit features include allowing marketers to meet their business goals by defining a target function (e.g. driving incremental sales vs. nurturing loyalty) and then simply deploying the engine to meet these goals.  Industry experts have called Summit “the most advanced data mining application ever deployed in a marketing environment”.

 

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Sagarmatha already influences tens of millions of consumers every week, delivering timely, highly-relevant offers that truly move shoppers to action. Contact us to see how we can reach and engage your shoppers, too.

Our Clients Include